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Dinsdag 12 november 2019
Prof.dr. P.H.E. Tiesinga (Neuroinformatics, Donders Institute for Brain, Cognition and Behaviour, Radboud Universiteit)
Understanding brains: biology versus nanotechnology
A fundamental goal of neuroscience is to understand how the brain works in terms of the electrical activity of its celllular constituents. It is not clear whether simple principles, characteristic of physical theories, would emerge for brain circuits — it is more likely that we can only understand it by building it using multimodal data derived from experiment. For a long time computational modeling of the brain was the only way of pursuing this approach. New developments in biology make possible so called brain-organoids, whereas progress in nanotechnology makes possible neuromorphic computing, both providing a means to build brains by physically modeling them in wet or hardware. The recent emergence of the field of artificial intelligence and deep learning provides yet another way to understand brains, but in terms of algorithms they might employ. I will discuss these different approaches to “build” brains in order to understand them and offer some opinions on how to make most progress. I will focus on the problem of connectomics, determining the wiring diagram of the brain, and the dynamic circuit motifs at the cellular level that emerge in real brains, which could in turn make artificial brains smarter.
Paul Tiesinga is currently Professor of Neuroinformatics at the Donders Institute at Radboud University, where he builds computational models of brain circuits and develops new methods to analyze brain signals. He studied physics at Utrecht University and received his PhD on a topic in theoretical condensed matter physics there as well. As postdoctoral fellow at Northeastern University (Boston) and the Salk Institute (La Jolla) he transitioned to research in computional neuroscience. His first faculty position was in the department of Physics & Astronomy at the University of North Carolina at Chapel Hill, from where he returned to the Netherlands to work at the Donders Institute.
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